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Figure.  Forest Plot of Year-Specific Estimates and Random-Effects Meta-analysis Summary Estimate of Heroin Dependence Within 1 to 12 Months of First Use
Forest Plot of Year-Specific Estimates and Random-Effects Meta-analysis Summary Estimate of Heroin Dependence Within 1 to 12 Months of First Use

This forest plot shows a preponderance of point estimates to the left of the random-effects meta-analysis summary estimate (vertical dashed line) before 2010 and to the right of the summary estimate after 2010. Outcomes were derived from a Taylor series linearization variance estimation that takes into account the complex multistage sampling plan with application of standard analysis weights. The percentage weight column discloses minor variation of the meta-analysis information weight based on the unweighted number of new heroin users each year, the proportion observed to have developed heroin dependence in 1 to 12 months, and its standard error.

1.
US Centers for Disease Control and Prevention; National Center on Health Statistics; National Vital Statistics System. Provisional counts of drug overdose deaths, as of 8/6/2017. https://www.cdc.gov/nchs/data/health_policy/monthly-drug-overdose-death-estimates.pdf. Published 2017. Accessed April 9, 2018.
2.
US Substance Abuse and Mental Health Services Administration; Center for Behavioral Health Statistics and Quality. Results from the 2016 National Survey on Drug Use and Health. https://www.samhsa.gov/sites/default/files/sites/default/files/2016_ffr_3_slideshow_v4.pdf. Published 2017. Accessed April 9, 2018.
3.
US Substance Abuse and Mental Health Services Administration; Center for Behavioral Health Statistics and Quality. Accessing national and state data from the National Survey on Drug Use and Health. https://archive.samhsa.gov/data/2k12/NSDUH116/NSDUHShortReport116AccessingData2012.htm. Published August 3, 2012. Accessed April 9, 2018.
4.
Martins  SS, Sarvet  A, Santaella-Tenorio  J, Saha  T, Grant  BF, Hasin  DS.  Changes in US lifetime heroin use and heroin use disorder: prevalence from the 2001-2002 to 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions.  JAMA Psychiatry. 2017;74(5):445-455.PubMedGoogle ScholarCrossref
5.
Parker  MA, Anthony  JC.  Epidemiological evidence on extra-medical prescription pain relievers: transitions from newly incident use to dependence among 12-21 year olds in the United States using meta-analysis, 2002-13.  PeerJ. 2015;3:e1340. doi:10.7717/peerj.1340Google ScholarCrossref
6.
Anthony  JC, Warner  LA, Kessler  RC.  Comparative epidemiology of dependence on tobacco, alcohol, controlled substances and inhalants: Basic findings from the National Comorbidity Survey.  Exp Clin Psychopharmacol. 1994;2(3):244-268.Google ScholarCrossref
Research Letter
August 2018

Risk of Heroin Dependence in Newly Incident Heroin Users

Author Affiliations
  • 1Department of Epidemiology and Biostatistics, Michigan State University, East Lansing
  • 2Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington
  • 3Vermont Center on Behavior and Health, University of Vermont, Burlington
JAMA Psychiatry. 2018;75(8):863-864. doi:10.1001/jamapsychiatry.2018.1214

Some 30 to 50 US residents die of heroin overdoses each day.1 By comparison, an estimated 300 to 520 individuals start heroin use each day.2 For first-time users, these odds of overdose death might seem remote. For this reason, clinicians and public health practitioners deserve more compelling evidence to share with people who contemplate trying heroin. Seeking reproducible results via 15 US epidemiological samples, we estimate how often newly incident heroin users become dependent on heroin. Estimation focuses on the first 1 to 12 months after first heroin use.

Methods

Each year from 2002 to 2016, the National Survey on Drug Use and Health (NSDUH) research staff drew a new US probability sample of noninstitutionalized civilians age 12 years and older. In each year, staff assessed heroin use and dependence using DSM-IV criteria via institutional review board–approved protocols for recruitment and standardized computer-assisted self-interviews.

The US Department of Health and Human Services Center for Behavioral Health Statistics and Quality created NSDUH open access analysis files with deidentified data after applying disclosure analyses designed to thwart reidentification of participants. Given the circumstances of open access and no contact with participants, the Michigan State University institutional review board ruled that plans to analyze these data qualified for the federal category “not human subjects research.”

Aggregate files included 837 326 participants, with 1021 identified as new heroin users. All were assessed approximately 1 to 12 months after first use.3 We estimated year-specific proportions for the chance of becoming dependent on heroin soon after heroin use onset, using StataMP13 (StataCorp) for calculus-derived standard errors and analysis weights. Expecting stable estimates,4 we used StataMP13 fixed-effects meta-analysis with heterogeneity evaluations. Seeing significant heterogeneity (I2 statistics with P < .05) and possible increasing estimates, we turned to DerSimonian-Laird random-effects estimation. The resulting meta-analysis fixed-effects summary estimates account for unmeasured methodological and/or substantive variation sources across samples year by year, with α set at .10.4 Additional details were published previously.5 We specified a contrast of estimates from 2006 to 2010 and from 2011 to 2016 before visual inspection and added estimates from 2002 to 2005 at the request of anonymous reviewers.

Results

The number of participants in the data sets ranged from 54 079 to 58 397 per year. Analysis weights made demographic variables balanced with US Census values year by year (eg, 48% male and 52% female). Participation was secured for more than 70% of designated respondents and more than 80% of sampled dwelling units. The Figure show general reproducibility across 15-year-specific estimates, with a random-effects meta-analysis summary estimate of 30.2% (95% CI, 22.9%-37.5%) becoming heroin dependent within approximately 1 to 12 months after heroin onset. In some recent years, larger point estimates are seen (Spearman ρ = 0.52; P = .052).

Heroin overdose death rates climbed after 2010.1 We specified random-effects meta-analysis comparisons of 2 intervals and found that, from 2006 to 2010, risk of dependence was 23.7% (95% CI, 16.8%-30.6%) vs 41.7% (95% CI, 35.3%-48.0%) from 2011 to 2016. We then explored 2002 to 2010 and derived an estimate of 20.1% (95% CI, 15.5%-24.7%). We compared the estimate of 20.3% (95% CI, 14.6%-25.9%) in 2002 to 2009 with 39.9% (95% CI, 31.4%-48.5%) from 2010 to 2016.

Discussion

When observed within approximately 1 to 12 months after heroin onset, an estimated 23% to 38% of new heroin users have become dependent on heroin. Rank-order correlation and post hoc exploratory analyses prompt a hypothesis of recently increased odds of becoming dependent on heroin.

Seeking estimates for comparison, we found 3 published studies on how often heroin dependence was found among people who have used heroin at least once in their lifetime. The National Comorbidity Survey (1990-1992) estimate was 23% dependence rate (with a standard error [SE] of 5%); National Epidemiologic Survey on Alcohol and Related Conditions (2001-2002) estimate (SE) was 28% (4%); and National Epidemiologic Survey on Alcohol and Related Conditions-III (2012-2013) estimate (SE) was 25% (2%).4,6 These 3 values yield a random-effects meta-analysis summary of 26%, with a 95% CI of 22% to 29%, which clearly overlaps this study’s overall finding of 23% to 38% of all participants becoming heroin dependent soon after first heroin use.

Limitations

In comparing this article with other surveys, differences in methods deserve consideration (eg, recall errors; cumulative odds of competing heroin dependence–associated risks, such as fatal overdose or incarceration; and left-truncation processes).5,6 In addition, estimates for 2002 through 2005 are from random-effects meta-analysis models and should be considered as post hoc exploratory data analyses completed after visual inspection of the year-specific estimates. Finally, all conclusions are subject to reevaluation when 2017 to 2018 NSDUH data files are released.

Conclusions

Irrespective of whether US heroin users now experience increased odds of becoming heroin-dependent, general principles indicate that primary prevention and early outreach initiatives are needed to control the spread of the nation’s current heroin epidemic. We now lack evidence-based interventions for new heroin users before dependence develops and before medication-assisted treatment is indicated. Neglect of new users might foster incrementally greater challenges and costs in the expansions of heroin dependence treatment service responses to the current public health emergency.

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Article Information

Corresponding Author: James C. Anthony, PhD, Department of Epidemiology and Biostatistics, Michigan State University, B601 West Fee, East Lansing, MI 48824 (janthony@msu.edu).

Published Online: May 30, 2018. doi:10.1001/jamapsychiatry.2018.1214

Author Contributions: Dr Anthony had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Anthony, Santiago Rivera.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Santiago Rivera, Havens, Anthony.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Santiago Rivera, Parker, Anthony.

Obtained funding: Anthony.

Administrative, technical, or material support: Santiago Rivera, Anthony.

Study supervision: Anthony.

Conflict of Interest Disclosures: None reported.

Funding/Support: Support for this study from 2014 to 2016 came from the National Institute on Drug Abuse (grant T32DA021129) and National Institute on Drug Abuse Senior Scientist and Mentorship Award (grant K05DA015799 to Dr Anthony).

Role of the Funder/Sponsor: Neither the National Institute on Drug Abuse nor the universities with which the authors are affiliated had any role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The content is the sole responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse, the National Institutes of Health, or Michigan State University.

Additional Contributions: These data are from open access public use data files that can be downloaded as Public Use Files from the US Substance Abuse and Mental Health Data Archive web site (https://pdas.samhsa.gov/#/). The authors agree to provide Stata do-files to create the study variables by request to the senior author (Dr Anthony).

References
1.
US Centers for Disease Control and Prevention; National Center on Health Statistics; National Vital Statistics System. Provisional counts of drug overdose deaths, as of 8/6/2017. https://www.cdc.gov/nchs/data/health_policy/monthly-drug-overdose-death-estimates.pdf. Published 2017. Accessed April 9, 2018.
2.
US Substance Abuse and Mental Health Services Administration; Center for Behavioral Health Statistics and Quality. Results from the 2016 National Survey on Drug Use and Health. https://www.samhsa.gov/sites/default/files/sites/default/files/2016_ffr_3_slideshow_v4.pdf. Published 2017. Accessed April 9, 2018.
3.
US Substance Abuse and Mental Health Services Administration; Center for Behavioral Health Statistics and Quality. Accessing national and state data from the National Survey on Drug Use and Health. https://archive.samhsa.gov/data/2k12/NSDUH116/NSDUHShortReport116AccessingData2012.htm. Published August 3, 2012. Accessed April 9, 2018.
4.
Martins  SS, Sarvet  A, Santaella-Tenorio  J, Saha  T, Grant  BF, Hasin  DS.  Changes in US lifetime heroin use and heroin use disorder: prevalence from the 2001-2002 to 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions.  JAMA Psychiatry. 2017;74(5):445-455.PubMedGoogle ScholarCrossref
5.
Parker  MA, Anthony  JC.  Epidemiological evidence on extra-medical prescription pain relievers: transitions from newly incident use to dependence among 12-21 year olds in the United States using meta-analysis, 2002-13.  PeerJ. 2015;3:e1340. doi:10.7717/peerj.1340Google ScholarCrossref
6.
Anthony  JC, Warner  LA, Kessler  RC.  Comparative epidemiology of dependence on tobacco, alcohol, controlled substances and inhalants: Basic findings from the National Comorbidity Survey.  Exp Clin Psychopharmacol. 1994;2(3):244-268.Google ScholarCrossref
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